	clear all
set more off
	
global dir = "C:\Users\mrueda\Documents\Emory\Papers\Networks_persistance\do_files\do_files_APSA21\post_JOP\Replication_BJPS\"	

cd "$dir"

use "Data\donor_level_persist_rep.dta",clear

keep if rank==1&family==0

replace b5=. if b2!=0


	texdoc close 
	cap erase "$dir/Tables/TableA3.tex"
	texdoc init "$dir/Tables/TableA3.tex", force


	tex \begin{table}[tbph]
	tex \caption{Contracts and next election donations (non-family members: logit results)}\label{tab:contracts_donation_l}
	tex \centering
	tex \begin{tabular}{lHcc c Hcc c HHH} \hline
	*tex Outcome: & \multicolumn{3}{c}{Any race} && \multicolumn{3}{c}{Mayor} && \multicolumn{3}{c}{Only mayor} \\ \cline{2-4} \cline{6-8} \cline{10-12}
	tex Outcome: & \multicolumn{3}{c}{Any race} && \multicolumn{3}{c}{Mayor} && \\ \cline{2-4} \cline{6-8} 
	tex & (1) & (1) & (2) && (4) & (3) & (4) && (7) & (5) & (6) \\ \hline
	tex & & & & & & & & & & &\\
	
	*Model 1
	foreach x in donate_15any b5{
	
		*Summary statistics for the mean
		quietly: logit `x' contract sanc_before ilegal p_prop elec_exp pol_exp_d center rank_don_alt_all lcont_donor_102 contraloria above_lim, vce(cluster muni_code)
		quietly sum `x' if e(sample)
			local mean_`x' : di %5.3f r(mean)
			local sd_`x' : di %5.3f r(sd) 
		
		*Regressions
		logit `x' contract sanc_before ilegal p_prop elec_exp pol_exp_d center rank_don_alt_all lcont_donor_102 contraloria above_lim, vce(cluster muni_code)
		
		local N_`x' : di %5.0f e(N)
		local ll_`x' : di %5.3f e(ll)

		matrix b = e(b)
		matrix v = e(V)
		matrix res=r(table)
		
		local b1_`x' : di %5.3f b[1,1]
		local se1_`x' : di %5.3f sqrt(v[1,1])
		local p_v_`x' :di %5.3f res[4,1]
		local uci_`x': di %5.3f res[6,1]
		local lci_`x': di %5.3f res[5,1]


		
		*T-statistics
		local t1_`x' = `b1_`x''/`se1_`x''
		local t1_`x' : di %5.3f  `t1_`x''
		
		
		*P-values
		local df : di `e(N)'-`e(k_absorb)'-`e(df_m)'-1
		scalar pval1_`x' = ttail(`df', abs(`t1_`x''))*2		

		

		
		*Reg with FE
		clogit `x' contract rank_don_alt_all lcont_donor_102 contraloria above_lim if e(sample),group(muni_code) vce(cluster muni_code)
		
		local dN_`x' : di %5.0f e(N)
		local dll_`x' : di %5.3f e(ll)
		
		matrix db = e(b)
		matrix dv = e(V)
		matrix dres=r(table)
		
		local db1_`x' : di %5.3f db[1,1]
		local dse1_`x' : di %5.3f sqrt(dv[1,1])
		local dp_v_`x' :di %5.3f dres[4,1]
		local duci_`x': di %5.3f dres[6,1]
		local dlci_`x': di %5.3f dres[5,1]

				
		*T-statistics
		local dt1_`x' = `db1_`x''/`dse1_`x''
		local dt1_`x' : di %5.3f  `dt1_`x''
		
		
		*P-values
		local df : di `e(N)'-`e(k_absorb)'-`e(df_m)'-1
		scalar dpval1_`x' = ttail(`df', abs(`dt1_`x''))*2


	}	
	


	tex  Contract & `ub1_donate_15any' & `b1_donate_15any' & `db1_donate_15any' && `ub1_b5' & `b1_b5' & `db1_b5' && `ub1_b3' & `b1_b3' & `db1_b3' \\
	tex  \ \ \ \ p-value & `up_v_donate_15any' & `p_v_donate_15any' & `dp_v_donate_15any' && `up_v_b5' & `p_v_b5' & `dp_v_b5' && `up_v_b3' & `p_v_b3' & `dp_v_b3' \\ 
	tex  \ \ \ \ CI 95\% & [`ulci_donate_15any',`uuci_donate_15any']& [`lci_donate_15any',`uci_donate_15any'] & [`dlci_donate_15any',`duci_donate_15any'] && [`ulci_b5',`uuci_b5'] & [`lci_b5',`uci_b5'] & [`dlci_b5',`duci_b5'] && [`ulci_b3',`uuci_b3'] & [`lci_b3',`uci_b3'] & [`dlci_b3',`duci_b3'] \\ \hline
	tex  % & (`use1_donate_15any') & (`se1_donate_15any') & (`dse1_donate_15any') && (`use1_b5') & (`se1_b5') & (`dse1_b5') && (`use1_b3') & (`se1_b3') & (`dse1_b3') \\ 	
		
	
	tex Observations & `uN_donate_15any' & `N_donate_15any' & `dN_donate_15any' && `uN_b5' & `N_b5' & `dN_b5' && `uN_b3' & `N_b3' & `dN_b3' \\
	tex Mean &   & `mean_donate_15any' &  `mean_donate_15any' &&  & `mean_b5' &`mean_b5'&& `mean_b3' & `mean_b3' & `mean_b3' \\
	*tex Effect Mean(\%) & `fem1_donate_15any' & `fem1_b5' & `fem1_b3' \\
	tex log-likelihood & `ull_donate_15any' & `ll_donate_15any' & `dll_donate_15any' && `ull_b5' & `ll_b5' & `dll_b5' && `ull_b3' & `ll_b3' & `dll_b3' \\
	tex Controls mayor& no & yes & no && no & yes &no && no & yes & no \\
	tex Controls donor& no & yes & yes && no & yes &yes && no & yes & yes \\
	tex Municipality FE & no & no & yes &&no & no & yes && no & no & yes \\ \hline
	tex \end{tabular}
	tex \parbox{150mm}{  \footnotesize{
	tex Estimates of the coefficient on receiving a contract in logit models of donating in the next election. Sample includes donors to the mayor. Columns 2 and 4 present conditional logit results with municipality as the grouping variable. Controls mayor denotes candidate's illegal registration of ID, being sanctioned, elected posts, ran as candidate past in elections, party has no clear ideological leaning, and non-family donations as a fraction of campaign revenue. Controls donor denotes logged value of donation, donated above legal limit, sanctioned, and donation rank among all donors. P-values and confidence intervals with clusters at the municipality level.
	tex }
	tex }
	tex \end{table}
	cap texdoc close 
	
	
	
***********Marginal effects for text
quietly: logit donate_15any contract sanc_before ilegal p_prop elec_exp pol_exp_d center rank_don_alt_all lcont_donor_102 contraloria above_lim, vce(cluster muni_code)
margins, dydx(contract) at(sanc_before=.1581306  ilegal=0 p_prop=.589134 elec_exp=.6325224 pol_exp_d=.4663892 center=1 rank_don_alt_all=6.15589 lcont_donor_102=1.436941 contraloria=0)

quietly: logit b5 contract sanc_before ilegal p_prop elec_exp pol_exp_d center rank_don_alt_all lcont_donor_102 contraloria above_lim, vce(cluster muni_code)
margins, dydx(contract) at(sanc_before=.1581306  ilegal=0 p_prop=.589134 elec_exp=.6325224 pol_exp_d=.4663892 center=1 rank_don_alt_all=6.15589 lcont_donor_102=1.436941 contraloria=0)	
	